Evidence map›Paper›PMID 27400691›Full record

ArticleDiabetologia2016

A novel approach for the analysis of longitudinal profiles reveals delayed progression to type 1 diabetes in a subgroup of multiple-islet-autoantibody-positive children.

David Endesfelder, Michael Hagen, Christiane Winkler, Florian Haupt, Stephanie Zillmer, Annette Knopff, Ezio Bonifacio, Anette-G Ziegler, Wolfgang Zu Castell, Peter Achenbach

Open access · bronzeAbstract read
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In one paragraph

Article in Diabetologia, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
5.7field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
  2. Article
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  4. Article
  5. Article
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  7. Review
  8. Article
  9. Dynamics of Islet Autoantibodies During Prospective Follow-Up From Birth to Age 15 Years.The Journal of clinical endocrinology and metabolism · 2020
    Article
  10. Article
  11. Modeling Disease Progression Trajectories from Longitudinal Observational Data.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020
    Article
  12. Birth and coming of age of islet autoantibodies.Clinical and experimental immunology · 2019
    Review
  13. Review
  14. Article
  15. Serum biomarkers for diagnosis and prediction of type 1 diabetes.Translational research : the journal of laboratory and clinical medicine · 2018
    Review
  16. Article
  17. Article
  18. Review
  19. Current Perspective on Auto-antibodies in Type 1 Diabetes.Indian journal of endocrinology and metabolism
    Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 6 institutions in 1 country.

David EndesfelderScientific Computing Research Unit, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Michael HagenScientific Computing Research Unit, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Christiane WinklerInstitute of Diabetes Research, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Florian HauptInstitute of Diabetes Research, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Stephanie ZillmerInstitute of Diabetes Research, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Annette KnopffInstitute of Diabetes Research, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Ezio BonifacioForschergruppe Diabetes e.V., Neuherberg, Germany.
Anette-G ZieglerInstitute of Diabetes Research, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany.
Wolfgang Zu CastellScientific Computing Research Unit, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany. castell@helmholtz-muenchen.de.
Peter AchenbachInstitute of Diabetes Research, Helmholtz Zentrum München, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany. peter.achenbach@helmholtz-muenchen.de.
Helmholtz Zentrum München · DEDeutsches Diabetes-Zentrum e.V. · DEHeinrich Heine University Düsseldorf · DEInstitute of Diabetes ResearchPaul Langerhans Institute Dresden · DETechnical University of Munich · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aims/hypothesisProgression to type 1 diabetes in children and adolescents is not uniform. Based on individual genetic background and environment, islet autoimmunity may develop at variable age, exhibit different autoantibody profiles and progress to clinical diabetes at variable rates. Here, we aimed to quantify the qualitative dynamics of sequential islet autoantibody profiles in order to identify longitudinal patterns that stratify progression rates to type 1 diabetes in multiple-autoantibody-positive children.

methodsQualitative changes in antibody status on follow-up and progression rate to diabetes were analysed in 88 children followed from birth in the prospective BABYDIAB study who developed multiple autoantibodies against insulin (IAA), GAD (GADA), insulinoma-associated antigen-2 (IA-2A) and/or zinc transporter 8 (ZnT8A). An algorithm was developed to define similarities in sequential autoantibody profiles and hierarchical clustering was performed to group children with similar profiles.

resultsWe defined nine clusters that distinguished children with respect to their sequential profiles of IAA, GADA, IA-2A and ZnT8A. Progression from first autoantibody appearance to clinical diabetes between clusters ranged from 6% (95% CI [0, 16.4]) to 73% (28.4, 89.6) within 5 years. Delayed progression was observed in children who were positive for only two autoantibodies, and for a cluster of 12 children who developed three or four autoantibodies but were IAA-negative in their last samples, nine of whom lost IAA positivity during follow-up. Among all children who first seroconverted to IAA positivity and developed at least two other autoantibodies (n = 57), the 10 year risk of diabetes was 23% (0, 42.9) in those who became IAA-negative during follow-up compared with 76% (58.7, 85.6) in those who remained IAA-positive (p = 0.004). CONCLUSIONS/

interpretationThe novel clustering approach provides a tool for stratification of islet autoantibody-positive individuals that has prognostic relevance, and new opportunities in elucidating disease mechanisms. Our data suggest that losing IAA reactivity is associated with delayed progression to type 1 diabetes in multiple-islet-autoantibody-positive children.

Indexed as

AlgorithmsAutoantibodiesCation Transport ProteinsCluster AnalysisDiabetes Mellitus, Type 1Disease ProgressionFemaleGlutamate DecarboxylaseHumansInsulinIslets of LangerhansMaleProspective StudiesZinc Transporter 8AutoantibodiesCation Transport ProteinsGlutamate DecarboxylaseInsulinSLC30A8 protein, humanZinc Transporter 8ClusteringIslet autoantibodyLongitudinalProfilesProgressionType 1 diabetes

Identifiers

PMID27400691
OpenAlexW2474852544

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.